WHY GENOME INDIA PROJECT MATTERS

THE CONTEXT: India, with its massive and diverse population, has been underrepresented in global genomic studies. The GenomeIndia Project (GIP) launched in 2020 aims to bridge this gap by sequencing whole genomes of 10,000 unrelated, healthy individuals from 83 population groups. The preliminary findings published in Nature Genetics in April 2025 mark a pivotal step toward developing population-specific medical strategies and understanding India’s evolutionary genetics.

GENESIS AND OBJECTIVES OF THE GENOME INDIA PROJECT

1. Origins and Timeline

• • Launch: Began in January 2020 to build a comprehensive gene bank for Indian populations.
  • Collaborating Institutions: A consortium of 20 research and academic institutions across India, including the Indian Institute of Science (IISc) Bengaluru, Centre for Cellular and Molecular Biology (Hyderabad), and Institute of Genomics & Integrative Biology (Delhi).
  • Scale of Study: Planned to study 10,000 individuals from 83 population groups, with blood samples and phenotype data collected from 20,000 individuals to create a robust genomic database.

 

2. Core Objectives

• • Mapping Genetic Diversity: To capture the genetic makeup of India’s numerous endogamous populations.
  • Facilitating Precision Medicine: To enable personalised healthcare solutions tailored to the Indian genetic landscape.
  • Investigating Population History: To understand patterns of migration, evolution, and adaptation among various ethnic and linguistic groups.
  • Informing Public Health Policies: To identify population-specific disease mutations and guide targeted interventions and drug development.

METHODOLOGY

1. Sample Collection and Representation

• • Population Groups: 83 groups (30 tribal and 53 non-tribal) spread across over 100 geographical locations.
  • Sampling Strategy:
    • Median of 159 samples from each non-tribal group and about 75 samples from each tribal group.
    • Focus on unrelated individuals to accurately capture mutation frequencies.
    • Inclusion of 3-6 parent-child pairs in each group to identify de novo (new) mutations.

 

2. Whole Genome Sequencing

• • DNA Samples: Out of 20,000 individuals, whole genome sequencing was conducted for 10,074 samples, though two populations were later excluded, leaving data from 9,772 individuals.
  • Institutions Involved in Sequencing:
    • Centre for Brain Research, IISc Bengaluru
    • Centre for Cellular and Molecular Biology, Hyderabad
    • Institute of Genomics & Integrative Biology, Delhi
    • National Institute of Biomedical Genomics, Kolkata
    • Gujarat Biotechnology Research Centre, Gandhinagar

 

3. Data Analysis and Publication

• • Preliminary Findings: Published in Nature Genetics (April 8), revealing key insights into mutations and population structure.
  • Future Publications: A comprehensive set of results is slated for release next year.

MAJOR FINDINGS

1. Genetic Variants

• • Scope: Approximately 180 million genetic variants identified across 9,772 individuals, belonging to 83 distinct groups.
  • Distribution:
    • 130 million in the 22 pairs of non-sex chromosomes (autosomes).
    • 50 million in sex chromosomes (X and Y).

 

2. Non-Coding Regions

• • Roughly 98% of the human genome comprises non-coding regions. Many of the 180 million variants are likely in these non-coding areas, which are vital for studying evolutionary history and gene regulation.

 

3. Population-Specific Insights

• • Endogamy: Centuries of endogamous practices have led to population-specific mutations and diseases.
  • Underrepresented in Global Databases: Indian populations, especially tribal groups, are severely underrepresented in global genomic studies, making GIP a key resource.

SIGNIFICANCE AND APPLICATIONS

1. Health and Medicine

• • Precision Medicine: By correlating specific genetic variants with diseases, treatments can be tailored to individual genetic profiles.
  • Disease Mapping: Identifying population-specific disease-causing mutations can guide public health policies and preventive measures.
  • Diagnostics and Therapeutics: Early detection tools and customised drugs can be developed for disorders common in Indian subpopulations (e.g., diabetes).

 

2. Population Evolution and Migration

• • Tracing Ancestry: Genetic data offer clues on how communities have migrated, merged, or remained isolated over generations.
  • Cultural-Linguistic Correlations: Since language and genetics are often interlinked, GIP helps in understanding the spread and evolution of language families (e.g., Indo-European, Dravidian, Austro-Asiatic, Tibeto-Burman).

 

3. Policy Implications

• • Targeted Public Health Interventions: Data-driven approaches to address disorders prevalent in specific groups (e.g., sickle cell disease in certain tribal communities).
  • Informed Resource Allocation: Governments can prioritise funding for research and healthcare in areas with higher genetic risk profiles.

 

4. Scientific Advancement

• • Global Collaboration: GIP fills a major gap in the Eurocentric global genomic databases, enabling broader genetic studies and international research partnerships.
  • Training and Capacity Building: Large-scale genomic projects enhance infrastructure, technology, and human resource capabilities within the country.

CHALLENGES AND LIMITATIONS

1. Under-Representation of Certain Groups

• • Although 83 population groups were included, some ancient populations (e.g., the Andaman tribes) and relatively modern populations were excluded in the present dataset.

 

2. Logistical and Ethical Complexities

• • Collecting and storing sensitive biological samples and phenotype data across remote areas involves ethical clearance, informed consent, and safe data handling.

 

3. Data Analysis and Interpretation

• • Large genomic datasets demand high-end computational infrastructure and advanced biostatistical expertise.
  • Interpreting non-coding region variations requires extensive longitudinal research and functional studies.

 

4. Scalability

• • While 10,000 genomes is significant, India’s vast population diversity may demand continued sampling to create a truly comprehensive repository.

THE WAY FORWARD:

1. Expanding Genetic Representation: Towards an Inclusive National Genome Framework

• • Launch a “Genomic Diversity Inclusion Mission” under the Ministry of Science & Technology to actively include:
    • PVTGs (Particularly Vulnerable Tribal Groups),
    • Andamanese Negrito populations (e.g., Jarwas, Onge),
    • Denotified tribes and nomadic groups with distinct genetic identities.
  • Inclusion will improve genetic risk mapping, reduce health disparities, and prevent policy myopia in preventive health schemes.
  • India hosts 705 tribal groups (Census 2011) and over 270 mother tongues (People’s Linguistic Survey of India); yet most remain genomically invisible.
  • Align with Global Genomic Initiatives like All of Us (USA) or H3Africa for comparative ancestry research.

 

2. Genomics in Public Health: Building a Precision Medicine Ecosystem

• •  Integrate genomics into National Health Mission 2.0, with phased introduction of:
    • Community Genomic Screening (for common disorders like thalassemia, BRCA mutations).
    • Disease-specific Genomic Panels for rural PHCs.
  • Andhra Pradesh’s genome-based sickle cell screening in tribal belts (2022) led to early interventions and reduced maternal mortality.
  • With Ayushman Bharat Digital Health ID for genotype-phenotype record integration.
  • Align with NITI Aayog’s Health System for a New India roadmap and WHO’s Precision Public Health model.

 

3. Ethical, Legal, and Social Framework (ELSI): Safeguarding Genetic Sovereignty

• • Solution:
    • Establish a National Genomic Ethics and Data Protection Authority (NGEDPA).
    • Make free, prior, informed consent and dynamic consent mandatory for tribal genomic research.
    • Pass a dedicated Genomic Data Protection Bill, with lessons from EU’s GDPR and India’s DPDP Act, 2023.

 

4. Infrastructure & Talent Development: The Genome Workforce of the Future

• • • Create a “National Genomic Science Fellowship” under DBT to train 5000 geneticists by 2030.
    • Establish regional Genomics Training and Innovation Centres (GTICs) in public universities.
  • Introduce genomics curriculum in MBBS and AYUSH education through National Medical Commission (NMC).
  • Singapore’s biomedical programme accelerated local genomic research ecosystem via targeted training.

 

5. Public–Private–Philanthropic Collaboration (3P Model): Innovation & Scalability

• • Solution:
    • Foster public–private co-development platforms (e.g., Bharat Biotech–IGIB collaboration for vaccine genomics).
    • Encourage philanthropic investment (e.g., Tata Trusts) to establish population genomics innovation hubs in underserved states.
  • Policy Tool: Create a National Genomics Innovation Fund (NGIF) within BIRAC to co-fund start-ups developing:
    • India-specific genetic diagnostics,
    • Population-linked AI risk prediction models,
    • Tribal tele-genetics platforms.

 

6. Targeted Public Health Strategy: Genomics to Reduce Health Inequities

• • Implement “Mission GENE-RAKSHA” for endemic rare disorders in tribal zones (e.g., congenital deafness in Arunachal, Tay-Sachs in some Kashmir groups).
  • Make carrier screening mandatory in public health services for diseases like thalassemia and sickle cell anemia.

THE CONCLUSION:

The GenomeIndia Project is a landmark initiative that holds the potential to revolutionize healthcare, anthropology, and biomedical research in India. By capturing the genetic uniqueness of Indian populations, it paves the way for equitable, affordable, and personalised healthcare. Its implications go beyond medicine—extending to national identity, policy-making, and innovation in the global South.

UPSC PAST YEAR QUESTION:

Q. What are the research and developmental achievements in applied biotechnology? How will these achievements help to uplift the poorer sections of the society? 2021

MAINS PRACTICE QUESTION:

Q. The GenomeIndia Project has the potential to democratise precision healthcare in India, but it also raises complex ethical and policy challenges.” Discuss in light of recent findings of the GenomeIndia Project.

SOURCE:

https://www.thehindu.com/sci-tech/science/how-will-genetic-mapping-of-indians-help-explained/article69443842.ece#:~:text=The%20data%20on%20variants%20associated,management%20of%20diseases%20in%20India.

https://indianexpress.com/article/explained/explained-sci-tech/genome-india-project-9938889/

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